slides from today's talk

1. MODEL TRANSFERS AND MOP

8. MESS and MOP
• Both have the intention of detecting
extrapolative situations
• MESS is implemented within Maxent
• MESS compares the area in question to the
centroid of the calibration cloud
• MOP compares the area in question to the
nearest part of the calibration cloud
• Agree on ‘out of range’ conditions
• MOP better characterizes similarities between
calibration and transfer regions, and thus is more
optimistic as regards in-range extrapolation

11. Ecological Niche
Conservatism
A. Townsend Peterson
University of Kansas

13. Charles Elton – niche as role
in communities
G. Evelyn Hutchinson –
multidimensional ecological niches,
bionomic versus scenopoetic variables

14. First Step: Reconcile Concepts

15. Abiotic niche
Biotic interactionsAccessibility
Area presenting
appropriate
combinations of
abiotic and
biotic conditions
(= potential
distribution)
Actual geographic distribution
(abiotic and biotic conditions fulfilled,
accessible to dispersers)

16. Second Step: Reconcile Scale

17. Third Step: Explore Patterns

20. Controversy and Debate I
“Overall, these results suggest a considerable role of
environmentally mediated divergence in speciation” – Graham et
al. 2004, Evolution
“Considerable debate has emerged in the recent literature as to
whether or not niches are conserved … We believe that the
question of whether niches are conserved or labile is not in itself
particularly fruitful.” – Wiens and Graham 2005, Ann. Rev. Ecol.
Evol. Syst.
“Several recent papers have mentioned that published studies on
environmental niche modelling do not consistently detect
phylogenetic signal, but these conclusions have been based on
relatively few studies … the evidence at hand does not support the
idea that phylogenetic signal should be the expected outcome of
evolutionary diversification.” – Losos 2008, Ecology Letters

25. A Gap in the Literature
• All previous reviews of niche conservatism
have reviewed examples without an explicit
temporal framework
• At time 0 – no differentiation
• At time -- plenty of differentiation (or all
species would be the same ecologically!)
• A review is needed, particularly in light of the
burgeoning literature, in which timescale is
included as explicitly as is feasible

27. Review
• 72 published studies
• 272 species
• Coarse-scale environmental features only
• Range-wide studies only
• Time scales
– Invasion – 100
– 102
years
– Longitudinal (short) – 101
– 102
years
– Across geographic range – 102
– 105
years
– Longitudinal (LGM-present) – 104
– 105
years
– Between sister species – 105
– 106
years
– Across closely related species – 105
– 106
years
– Across deeper phylogenetic lineage – 105
– 107
years

28. Timescale and Conservatism

29. Controversy and Debate II
“We show … that a shift of the observed climatic niche occurred
between native and non-native ranges … The models fail to predict
the current invaded distribution … Climate matching … may not
predict the full extent of invasions.” – Broennimann et al. 2007,
Ecology Letters
“… most studies investigating SDMs typically ignore prediction
errors and instead focus on regions where native distributions
correctly predict invaded ranges … Native range occurrences
under-predicted the invasive potential of fire ants, whereas
occurrence data from the US over-predicted the southern
boundary of the native range.” – Fitzpatrick et al. 2007, Glob. Ecol.
Biogeogr.

31. Aedes albopictus
• Known as the “Asian Tiger
Mosquito”
• Invader; fastest spreading
mosquito in the world
• Aggressive daytime biter
and pest
• Known to transmit
Dengue, La Crosse, St.
Louis, Eastern Equine,
Ross River, Rift Valley, and
West Nile Viruses

32. Aedes albopictus
Present predicted distribution, native range in Asia

33. Aedes albopictus:
USA invasion
Projected Asian niche into USA present to create
invasion risk-map. How well did GARP perform...

34. Aedes albopictus:
USA invasion

35. Aedes albopictus:
world risk-map

46. Warren et al. 2008, Evolution
• Point out that two contrasting null hypotheses
have been used
– that niches are more similar than some random
expectation
– that niches are identical
• Offer new quantitative metrics of niche similarity
and new quantitative approaches to testing
niche similarity versus difference
• Resolve one key aspect of the debate …
comparing apples and oranges

47. Timescale and Conservatism

48. Broennimann et al. - Centaurea
Fitzpatrick et al. - Solenopsis

49. Niche-equivalent Virtual Species

50. -4
-3
-2
-1
0
1
2
3
4
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3
North America
Close to Lawrence, Kansas

51. Niche-equivalent Virtual Species

52. Warren et al. Tests
• Observed Hellinger distance I = 0.4668
• Translation:
– The two niches are more similar than random expectations
– The two niches are significantly non-identical
– The “two” niches in reality were resampled from ONE niche!
• Conclusion:
– Tests of niche identity are too powerful statistically, and probably are
detecting differences that are not biologically significant
0
1
2
3
4
5
6
7
8
9
0.4 0.41 0.42 0.43 0.44 0.45 0.46 0.47
Niche Similarity Test

53. Bobwhite Colinus virginianus
0
5
10
15
20
25
30
0.74
0.76
0.78
0.80
0.82
0.84
0.86
0.88
0.90
Frequency
I
0
5
10
15
20
25
0.64
0.66
0.68
0.70
0.72
0.74
0.76
0.78
0.80
0.82
0.84
0.86
0.88
0.90
Frequency
Similarity value
D

54. Niche Equivalency – Warren et al.
“Peterson et al.’s (1999)
assertion that speciation across
the Isthmus of Tehuantepec
‘takes place in geographic, not
ecological, dimensions’ is
further challenged by rejection
of the hypothesis of niche
equivalency. This hypothesis is
rejected among sister species in
nearly every case, indicating
that significant environmental
niche differentiation occurs in
association with most speciation
events.”
BUT … Niche equivalency tests
are too powerful statistically.
Given sampling vagaries,
modeling variation, and the
highly complex and dimensional
nature of the environmental
space, essentially all pairs of
modeled niches will differ
significantly, as in
Broennimann’s and Fitzpatrick’s
analyses ... Are these differences
biologically significant?

56. Regarding methodological rigor in niche modeling …

57. ?
?

59. Conclusions I
• Niches DO evolve
• However:
• They do not evolve frequently or easily
• Niches are frequently conserved over time periods of
105
– 106
yr
• Evidence for associations between speciation
and niche evolution is not reliable
• Researchers have not taken care to characterize
fundamental ecological niches fully, differentiating
from existing subsets of niches
• Rigorous examples of niche evolution should be
sought, and would be of great interest

60. Niche Conservatism and Speciation
• Studies to date have not considered temporal
dimensions of niche conservatism versus
divergence
• Most studies to date do not distinguish the
fundamental ecological niche from the
existing fundamental niche
• Hence, studies to date over-estimate and
over-appreciate the potential for niche
evolution and its role in speciation

64. Can EVOLVECan EVOLVE Will change
with any
range
difference
Will change
with any
range
difference

65. Icterus
graceannae:
Known
occurrence
points on G

66. Raw points Distance filter Overlay elevation Hypothesis of M

67. Occurrences and M Rainfall Temperature Model outp

68. Model within M Cal in M, Trans to G Cal across G
ote that the two maps across all of G are surprisingly different from one anoth

69. Environmental variable value
Hutchinson’s
Dream
World
Environmental variable value
Wallace’s
Dream
World

70. Environmental variable value
Wallace’s
Dream
World
Conclusion: interpret only the portion of the response that is
represented within M, or risk making unsupported assertions

71. Correct conditions, indicated by occurrence data
Too cold, as indicated by no occurrences within M
Too warm? No evidence
within M

72. Too cold, good evidence,
though beyond η(M)
Too cold, good evidence
from within M
Suitable temperatures
Too hot??? No evidence
within M
Too cold, good evidence
from within M

73. Well-defined
niche limits
(upper and
lower)
Lower limit well-
defined, but
upper limit
undefinied.
Solution 1: treat
as missing data
in binned
analysis
Solution 2:
model and

74. ANCESTRAL STATE RECONSTRUCTION

78. CONTINUOUS CHARACTERS and
problems …

81. 1.0 1.1 1.2 1.3

82. 1.0 1.1 1.2 1.3

83. Well-defined
niche limits
(upper and
lower)
Lower limit well-
defined, but
upper limit
undefinied.
Solution 1: treat
as missing data
in binned
analysis
Solution 2:
model and

84. Geositta ovenbirds

88. Oriole example …

90. Model lower and upper limits as
continuous traits

93. Histogram of the
rate of Brownian
motion evolution
(σ2
) when
uncertainty is
considered. Blue =
value returned
when characters
are coded in M
only; magenta =
value returned
when models are
calibrated in M but
transferred across
G. designated by a
star. Slower rates
indicate less
evolution, whereas
faster rates
indicate more
evolution.

94. Bin and permit missing data

95. Well-defined
niche limits
(upper and
lower)
Lower limit well-
defined, but
upper limit
undefinied.
Solution 1: treat
as missing data
in binned
analysis
Solution 2:
model and

97. Niche Evolution Summary
• Fundamental niche is the evolvable quantity of
interest in studies of niche evolution
• Realized niche (or existing niche, or worse yet
sampled sites) is a mixture of effects of niche
evolution and effects of geography and
landscape
• Use of environmental characteristics of
occurrences, or uncareful niche models, in such
analyses will introduce considerable instability
• Better approach is to account for what is and is
not known directly and integrally in analyses

99. Biodiversity Informatics: making Primary
Biodiversity data available

100. Biodiversity Informatics Training
Curriculum Courses
• Data Capture
• Biodiversity Inventories
• Data Cleaning
• Data Publishing
• Biodiversity Data Analysis
• Species Descriptions
• Using R, QGIS, Refine,
EstimateS (under
development)
• Biostatistics (under
development)
• Public Health
Applications
• Ecological Niche
Modeling
• National Biodiversity
Diagnoses
• Conservation
Implementation
• Building Biodiversity
Informatics Institutions

101. Project Webpage

102. Communications - Facebook

103. Communications – Google+

104. Share Video - YouTube

105. Monthly Seminar

106. Interchange – Scientific Journal

107. BITC Version 1.2
• The curriculum is basically complete
– 507 videos make up the present curriculum version,
covering topics from data capture to building
institutions
– by end 2015, the final modules (R, Refine, EstimateS)
will be added
• The curriculum is available
– online via the project webpage
– in pdf format via Biodiversity Informatics
– on USB keys and in DVD formats (by request)

108. Links
• Town Peterson town@ku.edu
• BITC webpage
http://biodiversity-informatics-training.org
/
• Facebook
https://www.facebook.com/groups/Biodiv
/